«Paper No. 365 Determinants of self-employment among commuters and non-commuters Mikaela Backman Charlie Karlsson May, 2014 The Royal Institute of ...»
This kind of simple models can be extended by assuming heterogeneity among actors. Jackson and Rogers (2005) constructed a model where actors are brought together on ‘islands’, where the cost of establishing links on ‘islands’ are lower than the costs of establishing links between ‘islands’. With this model the authors are able to identify all stable networks and they find that all these networks are ‘small world’ networks as well as efficient networks. A second possible extension is the keep the assumption of complete heterogeneity and analyse the creation of networks as a dynamic process. Carayol and Roux (2009) models the formation of networks through a stochastic process disrupted by the establishment of links which makes it possible to analyse the structural attributes of the network equilibrium for different values of the distance decay function. They show that for a rather wide parameter value interval the network equilibrium is made up of ‘small world’ networks that are characterized by a high proportion of local links and a low average distance. In a somewhat earlier study Carayol, et al. (2008) use genetic algorithms and Monte Carlo simulations to get a better understanding of the characteristics of efficient networks and the instruments to determine the degree of inefficiency of created networks.
The connections’ models briefly described above have several common assumptions of which some may be questionable. One questionable assumption is that no learning is taking place, i.e., there is no increase in the different actors’ knowledge due to the interaction in the network. It is questionable because it has been stressed in the literature that repeated interaction between actors reduces the cognitive distance between them (Nooteboom 2004). When the knowledge base of actors become more similar due to repeated interaction, this might reduce to the willingness to continue to interact, since the options for further learning are reduced.
The possibility that actors might want to reduce interaction or even stop interacting with some other actors when the options for future learning are reduced is dealt with in a model by Cowan, et al. (2006), which integrates the ‘past-dynamic’ into the network creation process.
Here, the establishment and the destruction of links between firms is an ongoing process, which is influenced by the specific changing characteristics of firms following the interaction with other firms. At each stage of the process, every individual firm has a certain stock of knowledge and every firm deliberately chooses the firms with which is wants to interact. The motivation is that each firm through its interactions get an opportunity to combine its knowledge with the knowledge possessed by other firms and through that combination create new knowledge, which can be used to innovate. It such attempt has a certain probability to succeed and if it succeeds then the new knowledge created is used as an input in an innovation process. The newly created knowledge is also added to the firm’s knowledge stock. Interestingly, it is not in the interest of the firms to continue a successful interaction, since repeated interaction has a lower probability of generating a new innovation, since their knowledge bases are now more equal. On the other hand, a repeated interaction is connected with lower uncertainty and makes it easier for each partner to anticipate the behaviour of the other, i.e. interaction is becoming easier, which increases the probability of success.
It is possible to introduce a spatial perspective in the Cowan, et al. (2006) model. In the original model, interaction during an earlier period is the only factor that reduces the uncertainty of actors concerning the failure risk of any interaction. Spatial proximity between actors is another factor that probably tend to reduce the uncertainties among actors about if other actors can be trusted or not. It enables the diffusion of information about the reliability of actors that are potential interaction partners and increases the possibility of sanctions in case of disloyal behaviour. Thus, we can assume that actors have a higher probability to establish links with other actors nearby, ceteris paribus. Spatial proximity may even be a substitute for cognitive, technological and/or organizational proximity in order to increase the probability of a successful interaction and cooperation (Autant-Bernard et al. 2012).
The perhaps most important conclusion of the above discussion is that when actors self-organize and establish links and networks, these networks tends according to theoretical models to be ‘small world’ networks. From a spatial perspective this implies that self-organised networks mainly tend to develop at the level of localities even if of course some of the links can be to actors in other localities. We now turn to a discussion about the formation and characteristics of social networks that due to their character and dependence of face-to-face interactions naturally are ‘small world’ networks.
2.2 Social networks We start our discussion of social networks by defining and delineating three types of networks
for individuals that are working either as employees or as self-employed as follows:1
An individual’s private network is his/her links to other individuals in the (extended) family, friends and other acquaintances, i.e. the links representing expressive relations(Lincoln and Miller 1979). We here focus on those private links that can be utilized for economic purposes.
The business/work networks of an individual are here interpreted as the instrumental links (Lincoln and Miller 1979) an individual have to other individuals. These links can be limited to other people working at the same workplace but for many individuals the network also includes links to other individuals representing actual and potential customers and suppliers, where the supplier group not only includes links to suppliers of inputs in the form of goods and services but also links to providers of all kinds of business services including financial services but also other individuals representing various public administration organizations.
Professional networks, lastly, are instrumental links mainly related to an individual’s education, occupation and/or work tasks and includes links to individuals within occupational associations, trade unions, communities of practice, chambers of commerce, employers’ associations, Rotary, etc.
If we add an individual’s links in all these three networks together, we can talk about his/her social network. The social network allows an individual to draw on the information, knowledge, expertise, contacts and resources of other individuals and also get help and support from them (Burt 1992). Such a network represents an individual’s social capital, i.e. the Of course, an individual can have a link to another person trough more than one network.
actual and potential resources embedded within, available through and derived from the network of relations possessed by an individual (Coleman 1988; Uzzi 1996; Nahapiet and Ghoshal 1998). A critical factor of social networks is their density, since the density of social network links influence what kind of interactions, activities and transactions are made (Granovetter 1985). Individuals embedded in social networks can take advantage of very slowly changing institutional factors (Nyström 2012), such as a bounded solidarity, shared norms and values, common frameworks of reference, cultural rules, reciprocity, and enforceable trust that potentially function as a kind of social capital.
Embeddedness implies that social relations affect and shape the behaviour of the individuals in the network (Iandoli et al. 2014). It also implies that these individuals can safeguard their exchanges of information and knowledge and other resources as well as newly created knowledge and thus avoid the ‘information paradox’ (Arrow 1962) without using formal contracts (Jones et al. 1997). Social capital is here conceived as a system of shared values and beliefs that can prevent opportunistic behaviour by favouring trust building and cooperation among people (Putnam et al. 1993). The social network perspective emphasizes the cultural and institutional bases of the relationships between individuals (Granovetter 1985; Powell 1991).
Social networks provide information channels that are important sources of information and knowledge, since information and knowledge can flow relatively easy through such networks (Borgatti and Halgin 2011). Actually, it is a key characteristic of social networks that they involve privileged access to information and knowledge resources for the individuals in the network (Podolny and Page 1998) – information and knowledge that have been sorted and evaluated, so-called buzz (Bathelt et al. 2004). Empirical studies based upon the ‘connections’ model’ show that the links between actors are the basis for information and knowledge externalities and that information and knowledge flows from one actor to another decrease substantially when the distance within the network between two actors increases (Singh 2005;
Breschi and Lissoni 2006a).
For social networks as sources of information and knowledge it is important to consider that there are benefits from more diverse or “non-redundant” networks (Granovetter 1973). Thus, given that there are limits to the number of links that an individual can realistically establish and maintain, there is an information and knowledge advantage in a more diverse, less redundant social network in which the nodes to which an individual has links are not also connected to each other (Uzzi and Spiro 2005). Notions of the value of different links are also reflected in the distinction between weak and strong ties, whereby strong links are seen as more useful for help, support, and collaboration, whereas weak links are more useful as information and knowledge sources of creativity and innovation (Granovetter 1973; Burt 1992).
Social networks mainly tend to be geographically bounded, since the build-up and maintenance of personal links is strongly dependent upon frequent face-to-face interactions, and locational proximity reduces the costs and increases the frequency of personal contacts, which serve to build and to strengthen the social relations between the individuals in social networks (Dorfman 1987; Saxenian 1990; Almeida and Kogut 1997; Zucker et al. 1998) that also can be used for learning purposes (Almeida and Phene 2012). Breschi and Lissoni (2006b) show that the networks od interpersonal relations, which are the main vector for knowledge flows, appear to be concentrated locally. Thus, the interaction between the different individuals in a social network among other things is a function of the available material regional transport infrastructure, the functioning of the existing regional transport systems and the regional supply or arenas for meetings and interaction (Button et al. 1998; Karlsson and Manduchi 2001), i.e. a function of the regional factors that determine the foundations for regional accessibility and thus proximity. Certainly, some links can be long-distance but most links in these networks are due to the tyranny of distance short-distance links and regional proximity enhances the development of more complex social networks including common institutional and professional links (Graham 1985; Saxenian 1990; Almeida and Kogut 1999). Actually, research indicates the importance of geographically clustered social networks for the informal diffusion of information and knowledge (Rogers and Larsen 1984).
Links in social networks can be direct, i.e. an individual has a direct relationship to another individual or organization, or indirect, i.e. an individual has an indirect relationship to a third individual or organization via another individual or organization. An individual uses his/her network links to initiate and develop social relationships, to gather and to diffuse information and knowledge, etc. Individuals that are employed use their network links to interact with other people at the workplace, with customers and suppliers, with external people with similar interests, educations, occupations and work tasks, etc.
If we can turn to the mechanisms behind the formation of network links, we can point at education, common interests, living in the same neighbourhood and work, where the work links include both individuals at the same workplace and individuals at other work places within the same organization or at other organizations. Since we here are dealing with social links, i.e. links between individuals, it implies that the formation of links demand at least one personal meeting face-to-face.2 Thus, link activities (formation, maintenance and dissolution of links) are a function of the characteristics of individuals and their spatial behaviour, and of the spatial milieus where they are active. Personal link activities are generally driven by individual’s personal preferences. This implies that there is a tendency among individuals to connect with other individuals that are similar in different respects, which reduced the potential access to new information and knowledge through such links (McPherson et al. 2001). This implies that it probably is the business and professional links in an individual’s social network, i.e. the instrumental links that are developed via employment and/or self-employment that potentially will provide most new information and knowledge.